1. Technical field
The invention relates to a repetitive fusion search method for a search system.
2. Related Art
In over-the-counter sales for cosmetics, sales people have often talked with customers face-to-face, asked each customer about their needs, and proposed an article that meets them. Although this sales method provides an advantage in which an article that best matches a customer's needs can be proposed to the customer, it provides disadvantages in that salespeople have to have face-to-face communication with customers, so the employment cost for all of those salespeople is required and thus articles tend to be expensive. In addition, the salespeople only serve in their business hours, so customers cannot purchase their desired articles anytime and anywhere.
Meanwhile, major data searches include a keyword search using text and an instinct based search in which numerical value rating is given to each instinct based feature parameter for performing a search. For example, when cosmetics are sold online, customer needs need to be understood in detail so that an article that most meets the customer's needs can be extracted, proposed to the customer and purchased by the customer. However, understanding customer's needs in detail using the above key word search and instinct based search and extracting and proposing an article that most meets the customers needs based on the information has had a limitation and it has been difficult to realize online sales that achieve a high customer satisfaction level. In particular, in conventional instinct based searches, there is a deviation of customers' criterion for setting each instinct based feature parameter based on their instincts from a database creator's criterion for setting it, so the results desired by customers have not always been obtained. For example, even if a customer selects “a light color” for a certain article, the “light color” does not always match a manufacturer's “light color.”
Another recommendation system for online sales is also known (Patent Document 1: JP2004-341784 A). In this conventional recommendation system, even if a user searching for an article cannot find the article that he/she searches for, the system proposes articles that appear to suit the costumer's taste by proposing articles that have been checked by other users who selected similar articles in the past. However, in this conventional recommendation system, only articles that relate to search results are displayed, without considering the user's tastes and other attribute information, so only relating articles can be proposed, and articles that most meet the user's requirements cannot be proposed. In addition, a customer's needs cannot be understood through conversation with the customer, targeted articles cannot be specified properly.